A Path Planning Method for Biped Robot

Abstract

The invention discloses a path planning method for a biped robot. Orbslam2 based on a multi-source sensor RGBD is used to establish a 3D dense point cloud image, and Octomap is used to compress and filter ground information. Then the occupancy grid map is generated through 2D projection, and finally the cost map Costmap is used to add obstacle layer, and the improved D* and DwA are used for global and local path planning and navigation for real-time obstacle avoidance. This method adopts the integration of global and local path planning methods, and reduces unnecessary turning process by adding angle evaluation to the actual cost value of sub-nodes of D* algorithm, and at the same time, makes route planning safer and more reliable by limiting the selection of sub-nodes.

Description

technical field [0001] The invention relates to the field of robots, in particular to a path planning method for a biped robot. Background technique [0002] The existing path planning of mobile robots can be divided into global path planning and local path planning according to the map environment and obstacle types. Global path planning is mainly used to plan the path of the robot, and local path planning is mainly used for obstacle avoidance. The D* algorithm is a commonly used local path planning algorithm, but it has certain shortcomings in obstacle avoidance. The D* algorithm is a length-first algorithm and extends the search to the surrounding 8 child nodes. The generated path will damage the path quality. Unnecessary turns. In the actual navigation process, these unnecessary turns will increase the energy consumption and time of the mobile robot system. The length priority also causes the generated path to be very close to the obstacle. Sometimes it will start from ...

AI Technical Summary

Problems solved by technology

The D* algorithm is a commonly used local path planning algorithm, but it has certain shortcomings in obstacle avoidance. The D* algorithm is a length-first algorithm and extends the search to the surrounding 8 child nodes. The generated path will damage the path quality. Unnecessary turns. In the actual navigation process, these unnecessary turns will increase the energy consumption and time of the mobile robot system. The length priority also causes the generated path to be very close to the obstacle. Sometimes it will start from two "dangerous" obstacles. The safety and low energy consumption pursued by practical applications are not thoughtful

At the same time, general algorithms are generally written based on wheeled robots. To implement them in biped robots, certain conversions are required, which is not easy.

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